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Immunosignaturing is a new immunodiagnostic technology that uses random-sequence peptide microarrays to profile the humoral immune response. Though the peptides have little sequence homology to any known protein, binding of serum antibodies may be detected, and the pattern correlated to disease states. The aim of my dissertation is to analyze

Immunosignaturing is a new immunodiagnostic technology that uses random-sequence peptide microarrays to profile the humoral immune response. Though the peptides have little sequence homology to any known protein, binding of serum antibodies may be detected, and the pattern correlated to disease states. The aim of my dissertation is to analyze the factors affecting the binding patterns using monoclonal antibodies and determine how much information may be extracted from the sequences. Specifically, I examined the effects of antibody concentration, competition, peptide density, and antibody valence. Peptide binding could be detected at the low concentrations relevant to immunosignaturing, and a monoclonal's signature could even be detected in the presences of 100 fold excess naive IgG. I also found that peptide density was important, but this effect was not due to bivalent binding. Next, I examined in more detail how a polyreactive antibody binds to the random sequence peptides compared to protein sequence derived peptides, and found that it bound to many peptides from both sets, but with low apparent affinity. An in depth look at how the peptide physicochemical properties and sequence complexity revealed that there were some correlations with properties, but they were generally small and varied greatly between antibodies. However, on a limited diversity but larger peptide library, I found that sequence complexity was important for antibody binding. The redundancy on that library did enable the identification of specific sub-sequences recognized by an antibody. The current immunosignaturing platform has little repetition of sub-sequences, so I evaluated several methods to infer antibody epitopes. I found two methods that had modest prediction accuracy, and I developed a software application called GuiTope to facilitate the epitope prediction analysis. None of the methods had sufficient accuracy to identify an unknown antigen from a database. In conclusion, the characteristics of the immunosignaturing platform observed through monoclonal antibody experiments demonstrate its promise as a new diagnostic technology. However, a major limitation is the difficulty in connecting the signature back to the original antigen, though larger peptide libraries could facilitate these predictions.
ContributorsHalperin, Rebecca (Author) / Johnston, Stephen A. (Thesis advisor) / Bordner, Andrew (Committee member) / Taylor, Thomas (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Obesity impairs skeletal muscle maintenance and regeneration, a condition that can progressively lead to muscle loss, but the mechanisms behind it are unknown. Muscle is primarily composed of multinucleated cells called myotubes which are derived by the fusion of mononucleated myocytes. A key mediator in this process is the cellular

Obesity impairs skeletal muscle maintenance and regeneration, a condition that can progressively lead to muscle loss, but the mechanisms behind it are unknown. Muscle is primarily composed of multinucleated cells called myotubes which are derived by the fusion of mononucleated myocytes. A key mediator in this process is the cellular fusion protein syncytin-1. This led to the hypothesis that syncytin-1 could be decreased in the muscle of obese/insulin resistant individuals. In contrast, it was found that obese/insulin resistant subjects had higher syncytin-1 expression in the muscle compared to that of the lean subjects. Across the subjects, syncytin-1 correlated significantly with body mass index, percent body fat, blood glucose and HbA1c levels, insulin sensitivity and muscle protein fractional synthesis rate. The concentrations of specific plasma fatty acids, such as the saturated fatty acid (palmitate) and monounsaturated fatty acid (oleate) are known to be altered in obese/insulin resistant humans, and also to influence the protein synthesis in muscle. Therefore, it was evaluated that the effects of palmitate and oleate on syncytin-1 expression, as well as 4E-BP1 phosphorylation, a key mechanism regulating muscle protein synthesis in insulin stimulated C2C12 myotubes. The results showed that treatment with 20 nM insulin, 300 µM oleate, 300 µM oleate +20 nM insulin and 300 µM palmitate + 300 µM oleate elevated 4E-BP1 phosphorylation. At the same time, 20 nM insulin, 300 µM palmitate, 300 µM oleate + 20 nM insulin and 300 µM palmitate + 300 µM oleate elevated syncytin-1 expression. Insulin stimulated muscle syncytin-1 expression and 4E-BP1 phosphorylation, and this effect was comparable to that observed in the presence of oleate alone. However, the presence of palmitate + oleate diminished the stimulatory effect of insulin on muscle syncytin-1 expression and 4E-BP1 phosphorylation. These findings indicate oleate but not palmitate increased total 4E-BP1 phosphorylation regardless of insulin and the presence of palmitate in insulin mediated C2C12 cells. The presence of palmitate inhibited the upregulation of total 4EB-P1 phosphorylation. Palmitate but not oleate increased syncytin-1 expression in insulin mediated C2C12 myotubes. It is possible that chronic hyperinsulinemia in obesity and/or elevated levels of fatty acids such as palmitate in plasma could have contributed to syncytin-1 overexpression and decreased muscle protein fractional synthesis rate in obese/insulin resistant human muscle.
ContributorsRavichandran, Jayachandran (Author) / Katsanos, Christos (Thesis advisor) / Coletta, Dawn (Committee member) / Dickinson, Jared (Committee member) / Arizona State University (Publisher)
Created2017